Machine learning in absorption-based post-combustion carbon capture systems: A state-of-the-art review

M Hosseinpour, MJ Shojaei, M Salimi, M Amidpour - Fuel, 2023 - Elsevier
The enormous consumption of fossil fuels from various human activities leads to a significant
amount of anthropogenic CO 2 emission into the atmosphere, which has already massively …

[HTML][HTML] A systematic review of machine learning approaches in carbon capture applications

F Hussin, SANM Rahim, NSM Hatta, MK Aroua… - Journal of CO2 …, 2023 - Elsevier
Climate change and global warming are among of the most important environmental issues
and require adequate and immediate global action to preserve the planet for future …

Data-driven machine learning models for the prediction of hydrogen solubility in aqueous systems of varying salinity: Implications for underground hydrogen storage

HV Thanh, H Zhang, Z Dai, T Zhang… - International Journal of …, 2024 - Elsevier
Hydrogen is a clean and sustainable renewable energy source with significant potential for
use in energy storage applications because of its high energy density. In particular …

Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Journal of Industrial …, 2024 - Elsevier
This study explores the development of predictive models for carbon dioxide (CO 2)
solubility in ionic liquids based on a compiled dataset of 10,116 experimentally measured …

[HTML][HTML] Prediction the dynamic viscosity of MWCNT-Al2O3 (30: 70)/Oil 5W50 hybrid nano-lubricant using Principal Component Analysis (PCA) with Artificial Neural …

MH Esfe, M Hajian, D Toghraie, A Rahmanian… - Egyptian Informatics …, 2022 - Elsevier
In this study, the prediction of dynamic viscosity (µ nf) of MWCNT-Al 2 O 3 (30: 70)/Oil 5W50
hybrid nano-lubricant using Artificial Neural Network (ANN) is performed. The objective of …

Development of advanced model for understanding the behavior of drug solubility in green solvents: Machine learning modeling for small-molecule API solubility …

M Ghazwani, MY Begum, AM Naglah… - Journal of Molecular …, 2023 - Elsevier
Determination of small-molecule API (Active Pharmaceutical Ingredient) solubility in solvents
is of great importance for drug development in pharmaceutical industry. This study uses …

[HTML][HTML] Development of multiple machine-learning computational techniques for optimization of heterogenous catalytic biodiesel production from waste vegetable oil

WK Abdelbasset, SM Elkholi, MJC Opulencia… - Arabian Journal of …, 2022 - Elsevier
Multiple machine learning models were developed in this study to optimize biodiesel
production from waste cooking oil in a heterogenous catalytic reaction mode. Several input …

[HTML][HTML] Using halloysite nanotubes modified by tetraethylenepentamine for advanced carbon capture: experimental and modeling via RSM and ANNs

Z Khoshraftar, FS Taheri, S Nezami… - Chemical Engineering …, 2023 - Elsevier
In this research, halloysite nanotube was studied as a natural adsorbent for CO 2 capture.
The sorbents were prepared by the impregnation of several amounts of …

Implementation of AdaBoost and genetic algorithm machine learning models in prediction of adsorption capacity of nanocomposite materials

LI Weidong, MK Suhayb, L Thangavelu… - Journal of Molecular …, 2022 - Elsevier
Simulation of adsorption capacity of a nanocomposite material was performed in this study
in order to save time and cost in performing adsorption experiments. By develo** the …

[HTML][HTML] Predictive modeling and computational machine learning simulation of adsorption separation using advanced nanocomposite materials

X Hu, F Alsaikhan, HS Majdi, DO Bokov… - Arabian Journal of …, 2022 - Elsevier
Adsorption process was simulated in this study for removal of Hg and Ni from water using
nanocomposite materials. The used nanostructured material for the adsorption study was a …